CODEWITHSUNDEEP
javascalaapache-sparkapache-spark-sql
KAs
KAs

Reputation: 1868

java.lang.NoClassDefFoundError: Could not initialize class when launching spark job via spark-submit in scala code

I have a code which looks like below 

 object ErrorTest {
case class APIResults(status:String, col_1:Long, col_2:Double, ...)

def funcA(rows:ArrayBuffer[Row])(implicit defaultFormats:DefaultFormats):ArrayBuffer[APIResults] = {
  //call some API ang get results and return APIResults
  ...
}

// MARK: load properties
val props = loadProperties()
private def loadProperties(): Properties =  {
  val configFile = new File("config.properties")
  val reader = new FileReader(configFile)
  val props = new Properties()
  props.load(reader)
  props
}

def main(args: Array[String]): Unit = {
  val prop_a = props.getProperty("prop_a")

  val session = Context.initialSparkSession();
  import session.implicits._

  val initialSet = ArrayBuffer.empty[Row]
  val addToSet = (s: ArrayBuffer[Row], v: Row) => (s += v)
  val mergePartitionSets = (p1: ArrayBuffer[Row], p2: ArrayBuffer[Row]) => (p1 ++= p2)

  val sql1 =
    s"""
       select * from tbl_a where ...
     """

  session.sql(sql1)
    .rdd.map{row => {implicit val formats = DefaultFormats; (row.getLong(6), row)}}
    .aggregateByKey(initialSet)(addToSet,mergePartitionSets)
    .repartition(40)
    .map{case (rowNumber,rows) => {implicit val formats = DefaultFormats; funcA(rows)}}
    .flatMap(x => x)
    .toDF()
    .write.mode(SaveMode.Overwrite).saveAsTable("tbl_b")
  }
}

when I run it via spark-submit, it throws error Caused by: java.lang.NoClassDefFoundError: Could not initialize class staging_jobs.ErrorTest$. But if I move val props = loadProperties() into the first line of main method, then there's no error anymore. Could anyone give me a explanation on this phenomenon? Thanks a lot!

Caused by: java.lang.NoClassDefFoundError: Could not initialize class staging_jobs.ErrorTest$
  at staging_jobs.ErrorTest$$anonfun$main$1.apply(ErrorTest.scala:208)
  at staging_jobs.ErrorTest$$anonfun$main$1.apply(ErrorTest.scala:208)
  at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
  at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
  at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
  at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
  at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
  at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
  at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
  at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:243)
  at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:190)
  at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:188)
  at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1341)
  at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:193)
  ... 8 more

Upvotes: 12

Views: 18872

Answers (2)

Morrissss
Morrissss

Reputation: 324

I guess the problem is that val props = loadProperties() defines a member for the outer class (of main). Then this member will be serialized (or run) on the executors, which do not have the save environment with the driver.

Upvotes: 3

cnstevenyu
cnstevenyu

Reputation: 51

I've met the same question as you. I defined a method convert outside main method. When I use it with dataframe.rdd.map{x => convert(x)} in main , NoClassDefFoundError:Could not initialize class Test$ happened.

But when I use a function object convertor, which is the same code with convert method, in main method, no error happened.

I used spark 2.1.0, scala 2.11, it seems like a bug in spark?

Upvotes: 5

Related Questions